Google PCA Practice Test 30 — 15 Questions

Question 1

A financial services company needs a disaster recovery plan for a critical application running on GKE. The application uses Cloud SQL for MySQL. The RPO is 5 minutes and RTO is 15 minutes. Which design meets these requirements cost-effectively?

Accepted Answer

Use Cloud SQL cross-region replication (MySQL) with a failover replica in another region, and deploy GKE cluster in that region with the same configuration.. Cloud SQL cross-region replication provides an asynchronous replica in another region with a typical replication lag of a few seconds, meeting the 5-minute RPO. The failover replica can be promoted in minutes, and deploying a GKE cluster in the same region with identical configuration allows the application to connect to the promoted replica, achieving the 15-minute RTO. This approach is cost-effective because you only pay for the replica and the second GKE cluster when needed for failover testing or actual disaster recovery.

Answer

Use Cloud SQL for MySQL with multi-region database flag and route traffic to nearest region via Cloud Load Balancing.

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Set up VPC peering between two regions and use Cloud DNS to direct traffic in failover.

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Use Cloud SQL backups to Cloud Storage and restore in another region, with GKE cluster recreated via Deployment Manager.

Question 2

A developer is migrating a stateful application to GKE. The application requires persistent storage with high IOPS for a database. Which storage option is most suitable?

Accepted Answer

Persistent Disk SSD. Persistent Disk SSD (pd-ssd) is the most suitable option for a stateful database on GKE requiring high IOPS because it provides block storage with consistent, high-performance IOPS and can be dynamically provisioned via PersistentVolumeClaims. Unlike Local SSD, pd-ssd persists data independently of the node lifecycle, ensuring data durability during pod rescheduling or node failures.

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Local SSD

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Cloud Storage Fuse

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Persistent Disk Standard

Question 3

A company is using Cloud Storage for backups and wants to minimize costs. The backups are accessed infrequently and can tolerate retrieval delays. Which storage class is most appropriate?

Accepted Answer

Archive. Archive storage class is the most cost-effective option for backups that are accessed infrequently and can tolerate retrieval delays. It offers the lowest storage cost among Google Cloud Storage classes, with a default retrieval time of minutes to hours, making it ideal for long-term backup data that does not require immediate access.

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Standard

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Coldline

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Nearline

Question 4

A company runs a batch processing workload on Compute Engine. They need to minimize cost and ensure jobs complete within a 24-hour window. Which THREE strategies should they implement? (Choose 3.)

Accepted Answer

Use preemptible VMs for fault-tolerant jobs.. Preemptible VMs are significantly cheaper than standard VMs and are ideal for batch processing workloads that are fault-tolerant. Since the job can handle interruptions and be restarted, using preemptible VMs directly reduces cost while still completing within the 24-hour window if the job is designed to checkpoint progress.

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Use sole-tenant nodes for resource isolation.

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Configure instance reservations for guaranteed capacity.

Question 5

A company migrated their on-premises database to Cloud SQL and now experiences high latency for read-heavy workloads. How can they optimize performance?

Accepted Answer

Add read replicas.. Adding read replicas is the correct optimization because Cloud SQL read replicas offload read traffic from the primary instance, reducing latency for read-heavy workloads. Read replicas asynchronously replicate data from the primary using MySQL or PostgreSQL native replication, allowing queries to be distributed across multiple instances. This directly addresses the high latency by scaling read capacity horizontally without impacting write performance.

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Switch to a higher machine type.

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Enable automatic storage increase.

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Use connection pooling.

Question 6

A company runs a web application on Compute Engine instances. The application stores session state in files on local SSD. The company wants to reduce costs without sacrificing performance for a predictable traffic pattern. What should they do?

Accepted Answer

Use preemptible VMs in a managed instance group with autoscaling, and store session state in Redis (Memorystore).. Option A is correct because preemptible VMs reduce compute costs by up to 80%, and using a managed instance group with autoscaling handles the predictable traffic pattern efficiently. Storing session state in Redis (Memorystore) instead of local SSD ensures session data persists across VM preemptions and is shared among instances, which is critical for stateful applications. This combination maintains performance while eliminating the cost of always-on VMs.

Answer

Change the machine type to N2 standard and use committed use discounts.

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Keep local SSDs but use sole-tenant nodes to reduce contention.

Answer

Migrate the session state to Cloud Firestore and use preemptible VMs.

Question 7

A company wants to reduce Google Cloud costs for a batch processing workload. They currently use n1-standard-4 VMs running 24/7. The workload runs for 2 hours each night. What is the most cost-effective recommendation?

Accepted Answer

Use preemptible VMs with a startup script and persistent disk.. D is correct because the workload runs for only 2 hours per night, making preemptible VMs ideal — they cost up to 80% less than on-demand VMs and can be terminated at any time. A startup script ensures the job resumes if the VM is preempted, and using a persistent disk preserves data across interruptions. This combination provides the lowest cost for a short, fault-tolerant batch job.

Answer

Use on-demand VMs and rely on sustained use discounts.

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Use a custom machine type with fewer vCPUs.

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Use committed use discounts for 1 year.

Question 8

Which TWO actions can reduce costs for a Cloud SQL for MySQL instance? (Choose two.)

Accepted Answer

Use committed use discounts.. Committed use discounts (CUDs) provide significant cost savings (up to 57%) for Cloud SQL instances when you commit to a 1- or 3-year term. Resizing to a smaller machine type during off-peak hours directly reduces compute costs by lowering the vCPU and memory allocation when demand is low, and Cloud SQL supports live instance resizing with minimal downtime.

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Use database flags to limit connections.

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Use preemptible instances.

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Use high availability configuration.

Question 9

A team uses Cloud Build for CI/CD. The builds are taking longer than expected due to dependency downloads. What is the best practice to speed up builds?

Accepted Answer

Use Docker layer caching with Cloud Build by specifying a cache image or using Kaniko cache.. Option B is correct because Docker layer caching allows Cloud Build to reuse previously built layers, significantly reducing the time spent re-downloading and re-installing dependencies. By specifying a cache image or using Kaniko's built-in cache, only changed layers are rebuilt, while unchanged dependency layers are pulled from the cache instead of being fetched from the internet each time.

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Increase the machine type to e2-highcpu-32 to speed up compilation.

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Use Artifact Registry to store built packages and pull them during build.

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Store dependencies in Cloud Source Repositories and fetch them during build.

Question 10

A company is using Cloud CDN to accelerate content delivery. They notice increased costs from cache misses. What can they do?

Accepted Answer

Pre-cache popular content.. Pre-caching popular content ensures that the most frequently requested objects are already stored in Cloud CDN edge caches before users request them. This directly reduces cache misses because the content is proactively loaded, eliminating the need for the first user to trigger a fetch from the origin. By targeting high-demand assets, you minimize origin requests and lower the cost associated with cache misses.

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Use a larger cache size.

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Increase cache TTL.

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Use compression.

Question 11

A company runs batch processing jobs on a GKE cluster using preemptible node pools. The jobs are fault-tolerant and can be interrupted. However, the cluster is experiencing high costs due to underutilized nodes. The batch jobs run for 2-3 hours each. What is the most cost-effective optimization?

Accepted Answer

Create multiple node pools with different machine types and use node auto-provisioning with preemptible nodes and custom machine types.. Option D is the most cost-effective because it leverages node auto-provisioning with preemptible nodes and custom machine types, which dynamically creates node pools tailored to the specific resource requirements of each batch job. This eliminates waste from over-provisioned nodes while maintaining fault tolerance for interruptible workloads. Combined with preemptible instances (up to 60-80% cheaper than regular VMs), this approach minimizes cost without sacrificing job completion, as the jobs are already designed to handle interruptions.

Answer

Switch to compute-optimized (C2) machine types for faster job completion.

Answer

Use regional persistent disks for stateful workloads to improve performance.

Answer

Reduce the number of min-nodes in the node pool to zero during idle times and use cluster autoscaler.

Question 12

A company has a multi-region deployment of App Engine and wants to optimize request routing for latency and cost. Which GCP service should they use?

Accepted Answer

Cloud Load Balancing with global anycast.. Cloud Load Balancing with global anycast uses Google's global network and anycast IP addresses to route user traffic to the nearest healthy backend, minimizing latency. It also supports premium tier routing for lower latency and standard tier for lower cost, directly addressing the optimization goals for a multi-region App Engine deployment.

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Cloud Endpoints.

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Cloud DNS with latency-based routing.

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Cloud Traffic Director.

Question 13

A company has an on-premises data center connected to GCP via Dedicated Interconnect. They run latency-sensitive applications on GCE and use Cloud Storage for backups. The backup traffic is causing congestion on the Interconnect link. How should they optimize costs and performance?

Accepted Answer

Route backup traffic through a separate VPN tunnel over the internet to reduce congestion on the Interconnect.. Option D is correct because routing backup traffic over a separate VPN tunnel using the internet offloads non-latency-sensitive backup data from the Dedicated Interconnect link, reducing congestion without incurring additional costs for increased bandwidth. This approach preserves the low-latency path for critical application traffic while using a cost-effective, encrypted internet-based connection for backups, optimizing both performance and cost.

Answer

Increase the Dedicated Interconnect bandwidth to accommodate both traffic types.

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Move backup storage to a different region to reduce data transfer costs.

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Use Cloud Interconnect to connect directly to Cloud Storage for backup traffic.

Question 14

A Cloud Spanner instance is experiencing high latency for point reads. The instance has 5 nodes and the read throughput is moderate. The table has a primary key with monotonically increasing values. What is the most likely cause and optimization?

Accepted Answer

The primary key design causes hotspotting; use a hash prefix or add a leading random value.. The monotonically increasing primary key causes all writes to be directed to the last tablet (splitting point), creating a hotspot on one node. This hotspot leads to high latency for point reads because that node becomes a bottleneck. Adding a hash prefix or a leading random value distributes writes and reads evenly across all nodes, resolving the hotspotting issue.

Answer

Use interleaved tables to reduce the number of index lookups.

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The instance is underprovisioned; add more nodes.

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The instance has too many nodes causing transaction conflicts; reduce nodes.

Question 15

You are running a Cloud Run service that experiences occasional cold starts causing latency spikes. You want to minimize cold starts cost-effectively. What should you do?

Accepted Answer

Set min-instances to 1 to keep at least one instance always warm.. Setting min-instances to 1 ensures that at least one instance of your Cloud Run service is always kept warm, meaning it is initialized and ready to handle requests immediately. This eliminates cold starts for the first request after a period of inactivity, reducing latency spikes without requiring over-provisioning of resources. It is cost-effective because you only pay for the idle instance when it is not serving traffic, and you avoid the higher costs of larger machine types or excessive concurrent instances.

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Increase the max-instances setting to allow more concurrent requests.

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Set concurrency to 1 to ensure each instance handles one request at a time.

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Use a larger machine type (e.g., 2 vCPU) to reduce startup time.